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Paper Citation Record · LEDGER

Feedbackward Decoding for Semantic Segmentation

As of 15 August 2026, this Paper Citation Record lists 30 of 30 outbound references and 0 inbound Pith citation observations for arXiv:1908.08584.

A citation records a reference. It does not transfer a finding from one paper to another.

pith.paper-citation-record.v1
1908.08584 v1

Coverage vector

measured 30 of 30 reference resolution

Typed states for the displayed outbound observations.

Source: paper_references, paper_reference_links, observed 2026-08-14T11:39:59.534119Z

measured 30 of 30 standing notices

One-hop event checks from named stored sources.

Source: scholarly_work_events, retraction_status_cache, observed 2026-08-15T06:32:42.880941+00:00

measured 0 of 0 inbound itemization

Pith citing papers itemized under the disclosed page cap.

Source: paper_references, paper_reference_links

measured 0 of 1 external citation measurements

A source-named dated measurement, never combined with another source.

Source: cited_works

Reference resolution

30 of 30 outbound references displayed

  • verified exact1
  • verified fuzzy2
  • unresolved27
  • parse uncertain0
  • malformed identifier0
  • metadata mismatch0

External citation measurements

No source-named external measurement is stored.

Outbound references

Observation eab8ff67-c6e0-48ef-811b-3c387a341400 · outbound

This paper cites write newline.

Feedbackward Decoding for Semantic Segmentation write newline

Reference 1

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no resolver link, observed 2026-08-14T11:39:59.424774Z

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Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-14T11:39:59.424774Z digest=sha256:aa6a78a1d08bc86b04c0421fac310ff3cf75f5529bcba019657cf4fff6d73b26

Observation 6db697e1-95ae-434e-abca-7067bdf1fabd · outbound

This paper cites SegNet: A Deep Convolutional Encoder-Decoder Architecture for Image Segmentation.

Feedbackward Decoding for Semantic Segmentation SegNet: A Deep Convolutional Encoder-Decoder Architecture for Image Segmentation

Reference 2

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no resolver link, observed 2026-08-14T11:39:59.430314Z

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source=arxiv_source observed=2026-08-14T11:39:59.430314Z digest=sha256:c6ca70574569f28afe23d00643fc0d251930ccaf5b68bb18bc9a3a582ee039de

Observation 5672e5b4-a0de-4f37-99fb-4779364d01b1 · outbound

This paper cites Brostow, Julien Fauqueur, and Roberto Cipolla.

Feedbackward Decoding for Semantic Segmentation Brostow, Julien Fauqueur, and Roberto Cipolla

Reference 3

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no resolver link, observed 2026-08-14T11:39:59.434558Z

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source=arxiv_source observed=2026-08-14T11:39:59.434558Z digest=sha256:dc59a1fd5519c4f0b1860169d8562fda6d3b0e6cf8e75ece5b5c5e6a86dc052c

Observation 39f25d95-ae94-4613-bed3-24a6e601300d · outbound

This paper cites Semantic Image Segmentation with Deep Convolutional Nets and Fully Connected CRFs.

Feedbackward Decoding for Semantic Segmentation Semantic Image Segmentation with Deep Convolutional Nets and Fully Connected CRFs

Reference 4

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source=arxiv_source observed=2026-08-14T11:39:59.438554Z digest=sha256:0dabece991649fce503abded19f65e81d37501461bab627c3e661eac2f0e7f98

Observation af42a6e5-9cff-4719-b6e9-2f32ca4061c5 · outbound

This paper cites DeepLab: Semantic Image Segmentation with Deep Convolutional Nets, Atrous Convolution, and Fully Connected CRFs.

Feedbackward Decoding for Semantic Segmentation DeepLab: Semantic Image Segmentation with Deep Convolutional Nets, Atrous Convolution, and Fully Connected CRFs

Reference 5

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source=arxiv_source observed=2026-08-14T11:39:59.442633Z digest=sha256:1686068313180dc61af67d9d135dde63e375d634e6cf2cdc85083aa109a8e67c

Observation 9b40ee2e-d54e-45ad-8f0b-542fd1fbce92 · outbound

This paper cites Rethinking Atrous Convolution for Semantic Image Segmentation.

Feedbackward Decoding for Semantic Segmentation Rethinking Atrous Convolution for Semantic Image Segmentation

Reference 6

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no resolver link, observed 2026-08-14T11:39:59.447649Z

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source=arxiv_source observed=2026-08-14T11:39:59.447649Z digest=sha256:8bc473d93e34a82c1659c9fa554681bca1c6df273ba0fecb2ea6b4c58af36a5f

Observation 0cb0f675-1f3b-4969-bbea-04c43d0fe791 · outbound

This paper cites Encoder-Decoder with Atrous Separable Convolution for Semantic Image Segmentation.

Feedbackward Decoding for Semantic Segmentation Encoder-Decoder with Atrous Separable Convolution for Semantic Image Segmentation

Reference 7

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source=arxiv_source observed=2026-08-14T11:39:59.451654Z digest=sha256:a61ad186ca329c36859d46ee4ecdecd407d986664d9d8aa88e6a5873fa0f2a4a

Observation 4150c4dd-3bb7-4bc8-bb40-475570d8e5ed · outbound

This paper cites Xception: Deep Learning with Depthwise Separable Convolutions.

Feedbackward Decoding for Semantic Segmentation Xception: Deep Learning with Depthwise Separable Convolutions

Reference 8

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source=arxiv_source observed=2026-08-14T11:39:59.455734Z digest=sha256:ea96219aa53ab234306dcf8c3200cdf571a70acabc76e200fd166581bde01873

Observation 56ead764-0ca9-4a2a-ae61-ab7b71cec11f · outbound

This paper cites The Cityscapes Dataset for Semantic Urban Scene Understanding.

Feedbackward Decoding for Semantic Segmentation The Cityscapes Dataset for Semantic Urban Scene Understanding

Reference 9

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source=arxiv_source observed=2026-08-14T11:39:59.459523Z digest=sha256:56156267ccc97f93e1c1ba7ea52a7efdbdf6859f2e79735ed282a17bc814aa90

Observation 873c2cce-6e35-46ee-9117-651b0289119e · outbound

This paper cites A guide to convolution arithmetic for deep learning.

Feedbackward Decoding for Semantic Segmentation A guide to convolution arithmetic for deep learning

Reference 10

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source=arxiv_source observed=2026-08-14T11:39:59.462975Z digest=sha256:0be8d85d9534d0028c699042a0fe7cad52ca7795a63d7d6f67e3590602976821

Observation f9a289fc-0349-48cb-bdf2-2b22167c7957 · outbound

This paper cites Deep Learning.

Feedbackward Decoding for Semantic Segmentation Deep Learning

Reference 11

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source=arxiv_source observed=2026-08-14T11:39:59.466886Z digest=sha256:cdbbfe72199842d8d61b46b721ab2c72d4433369584291c4760cb2051eb8b1d7

Observation 95a4a8a7-5dc5-4dcc-8310-ba4449f092a1 · outbound

This paper cites Deep Residual Learning for Image Recognition.

Feedbackward Decoding for Semantic Segmentation Deep Residual Learning for Image Recognition

Reference 12

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source=arxiv_source observed=2026-08-14T11:39:59.471138Z digest=sha256:b30d5a54d7aa7a4ea4e65843796865d77276bdd012cca374ec1b20236c442776

Observation e9c80138-2d5f-4aff-825f-7469d240cf33 · outbound

This paper cites Batch Normalization: Accelerating Deep Network Training by Reducing Internal Covariate Shift.

Feedbackward Decoding for Semantic Segmentation Batch Normalization: Accelerating Deep Network Training by Reducing Internal Covariate Shift

Reference 13

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source=arxiv_source observed=2026-08-14T11:39:59.474991Z digest=sha256:a4c0957b1c911beea1b60f34db5bcd53b20f11f2de50e4d4551f1402a96c0439

Observation 97afb6ec-ec6b-4b63-bc56-b63ace86098f · outbound

This paper cites Adam: A Method for Stochastic Optimization.

Feedbackward Decoding for Semantic Segmentation Adam: A Method for Stochastic Optimization

Reference 14

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source=arxiv_source observed=2026-08-14T11:39:59.478537Z digest=sha256:1423ab159ebdd29553bf6bd6e5dfa4fdcd6679bb47a87a05deab26a1182fb4de

Observation 355f250f-87fc-4095-b4fd-30a4b4d0bc44 · outbound

This paper cites RefineNet: Multi-Path Refinement Networks for High-Resolution Semantic Segmentation.

Feedbackward Decoding for Semantic Segmentation RefineNet: Multi-Path Refinement Networks for High-Resolution Semantic Segmentation

Reference 15

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source=arxiv_source observed=2026-08-14T11:39:59.481850Z digest=sha256:5c8dbc9722520e57e356cfe532ab9c90bda07b40c4b996be5b552a8833afe2c9

Observation e676443a-4474-4149-bf38-45721b4236c9 · outbound

This paper cites Recent progress in semantic image segmentation.

Feedbackward Decoding for Semantic Segmentation Recent progress in semantic image segmentation

Reference 16

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verified exact
local_arxiv, observed 2026-08-14T11:39:59.725758Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-15T06:32:42.880941+00:00.

source=arxiv_source observed=2026-08-14T11:39:59.485222Z digest=sha256:12c9f75710061f2e77e9eef5fccc4f666a9ed0cfb99c14bab86d665962878956

Observation 84316135-26ac-41fa-a2e1-6ec68cef43c6 · outbound

This paper cites Fully Convolutional Networks for Semantic Segmentation.

Feedbackward Decoding for Semantic Segmentation Fully Convolutional Networks for Semantic Segmentation

Reference 17

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source=arxiv_source observed=2026-08-14T11:39:59.488522Z digest=sha256:5791c7dadf8c7f0e290b53e6785df1aee0a9bb8fb2ec80ca0b588dc641888621

Observation 9f39efd7-0472-4fa9-8cb9-d656b73eed01 · outbound

This paper cites Balak, Pavel Karas, Tereza Bolcková, Markéta Štreitová, Craig Carthel, Stefano Coraluppi, Nathalie Harder, Karl Rohr, Klas E.

Feedbackward Decoding for Semantic Segmentation Balak, Pavel Karas, Tereza Bolcková, Markéta Štreitová, Craig Carthel, Stefano Coraluppi, Nathalie Harder, Karl Rohr, Klas E

Reference 18

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source=arxiv_source observed=2026-08-14T11:39:59.492187Z digest=sha256:7eb17c664740db8bc022d13d498adcb4f76c9f087df8e28bd07b6a8e0d99062f

Observation 5afc245f-1e32-4997-a257-9d74996783ab · outbound

This paper cites The Natural Language Decathlon: Multitask Learning as Question Answering.

Feedbackward Decoding for Semantic Segmentation The Natural Language Decathlon: Multitask Learning as Question Answering

Reference 19

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source=arxiv_source observed=2026-08-14T11:39:59.495503Z digest=sha256:4b6a1bac6bf433a7f9fc7a733868c287c57d5b029f32944cc65643c24eb3eecd

Observation 9e8f81c1-a402-4a24-9278-70b36e1357a1 · outbound

This paper cites an unresolved cited work.

Feedbackward Decoding for Semantic Segmentation Unresolved cited work

Reference 20

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source=arxiv_source observed=2026-08-14T11:39:59.499217Z digest=sha256:fef90d45f9753ce61f27644a90dc430d8c34812626c418f8454f006f351daadf

Observation 0d54f88b-3758-4507-a771-858d4b6aade5 · outbound

This paper cites The mapillary vistas dataset for semantic understanding of street scenes.

Feedbackward Decoding for Semantic Segmentation The mapillary vistas dataset for semantic understanding of street scenes

Reference 21

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verified fuzzy
raw_fallback, observed 2026-08-14T11:39:59.855896Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-15T06:32:42.880941+00:00.

source=arxiv_source observed=2026-08-14T11:39:59.502284Z digest=sha256:f9e2475841149d43f391eecfc30ee4a58275ecbb6273c3aeb395a2255214fb55

Observation 8a8e1cba-3223-4828-94fd-cef081449cc5 · outbound

This paper cites Deconvolution and checkerboard artifacts.

Feedbackward Decoding for Semantic Segmentation Deconvolution and checkerboard artifacts

Reference 22

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source=arxiv_source observed=2026-08-14T11:39:59.505697Z digest=sha256:c0fe943d37f5574436eb801f601a94b3416f6837c89d38ec6b57a766999edb64

Observation fb7c019e-2ecf-4771-bbc2-4ea1d98e4e64 · outbound

This paper cites Optimizing intersection-over-union in deep neural networks for image segmentation.

Feedbackward Decoding for Semantic Segmentation Optimizing intersection-over-union in deep neural networks for image segmentation

Reference 23

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verified fuzzy
raw_fallback, observed 2026-08-14T11:39:59.845230Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-15T06:32:42.880941+00:00.

source=arxiv_source observed=2026-08-14T11:39:59.509293Z digest=sha256:ce4ef6209496c706f753196198148b01a5453f1e5438f0298d24b70c3833fb77

Observation b4b0a843-4669-4cc0-95b3-bd11f66ef8b6 · outbound

This paper cites YOLO9000: Better, Faster, Stronger.

Feedbackward Decoding for Semantic Segmentation YOLO9000: Better, Faster, Stronger

Reference 24

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source=arxiv_source observed=2026-08-14T11:39:59.512994Z digest=sha256:5563e67861a775f7a7d2fa1eb278fdb600608f8d0264344aae04883b74eed522

Observation 49aa9ac3-7627-4746-b6c3-dbc1a8aa48a4 · outbound

This paper cites YOLOv3: An Incremental Improvement.

Feedbackward Decoding for Semantic Segmentation YOLOv3: An Incremental Improvement

Reference 25

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source=arxiv_source observed=2026-08-14T11:39:59.516655Z digest=sha256:924fa99008c1850baa7a53e0128c5ccc0e10945603d6c17de05df5bd06bca075

Observation 29325490-f5c1-436c-84cb-1e5c557a6a6d · outbound

This paper cites You Only Look Once: Unified, Real-Time Object Detection.

Feedbackward Decoding for Semantic Segmentation You Only Look Once: Unified, Real-Time Object Detection

Reference 26

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Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-14T11:39:59.520244Z digest=sha256:4309b8f25f9f61f83ce80b65da0e0c87583f9eb6ccda358179fbf4172c77f8ad

Observation 06f01880-b7d7-4268-a2f5-d9f59c1842ae · outbound

This paper cites U-Net: Convolutional Networks for Biomedical Image Segmentation.

Feedbackward Decoding for Semantic Segmentation U-Net: Convolutional Networks for Biomedical Image Segmentation

Reference 27

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Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-14T11:39:59.524193Z digest=sha256:01125ffe4cd60001f6238f6f3080b31271c460aa7d004de33af8c9734a9966ee

Observation 9a6d9a38-02b3-4d72-a0c6-7947c470988f · outbound

This paper cites ImageNet Large Scale Visual Recognition Challenge.

Feedbackward Decoding for Semantic Segmentation ImageNet Large Scale Visual Recognition Challenge

Reference 28

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Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-14T11:39:59.527437Z digest=sha256:c98f37c0dcb1f5913ee1d93ffd93b645cbcc59e5794270dde4ae9aa77a4fa89d

Observation b0756121-c7d2-4566-9893-36ea08a8bc66 · outbound

This paper cites Very Deep Convolutional Networks for Large-Scale Image Recognition.

Feedbackward Decoding for Semantic Segmentation Very Deep Convolutional Networks for Large-Scale Image Recognition

Reference 29

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Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-14T11:39:59.530731Z digest=sha256:0ecce9f51d2a7e494bc72da373e888ba3eb3b79a031de85e42a5b396f2cc043d

Observation 4163582d-097f-46e3-88bd-fb4889cced11 · outbound

This paper cites Multi-Scale Context Aggregation by Dilated Convolutions.

Feedbackward Decoding for Semantic Segmentation Multi-Scale Context Aggregation by Dilated Convolutions

Reference 30

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unresolved
no resolver link, observed 2026-08-14T11:39:59.534119Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-14T11:39:59.534119Z digest=sha256:6377ff74e4ff7a8df0cae55c05ef8d39cef39196c7f71f3235e1165021056cbc

Pith citing papers

No inbound Pith citation observations are available.